Application of Neural Network for the Prediction of Eco-efficiency

This paper presents the application of neural networks in the design process of new technologies taking into account factors such as their influence on the environment and the economic effects of their implementation. The use of neural networks allowed eco-efficiency assessment of technologies based on highly reduced number of descriptive design parameters, which are very difficult to collect at the conceptual design stage. The great diversity of technologies involved along with the small number of available examples made difficult to construct a neural model and demanded careful data preprocessing and network structure selection.

[1]  David Wallace,et al.  Product classification to support approximate life-cycle assessment of design concepts , 2006 .

[2]  Kwang-Kyu Seo,et al.  Approximate Life Cycle Assessment of Product Concepts Using a Hybrid Genetic Algorithm and Neural Network Approach , 2006, ICHIT.

[3]  David Taniar,et al.  Computational Science and Its Applications - ICCSA 2005, International Conference, Singapore, May 9-12, 2005, Proceedings, Part I , 2005, ICCSA.

[4]  Tadeusz Wieczorek,et al.  An algorithm of knowledge extraction from trained neural networks , 2004, Intelligent Information Systems.

[5]  Jan Wachowicz,et al.  A life cycle method for assessment of a colliery’s eco-indicator , 2004 .

[6]  Chun-Wu Yeh,et al.  A non-parametric learning algorithm for small manufacturing data sets , 2008, Expert Syst. Appl..

[7]  Hun-Woo Yoo,et al.  Artificial Neural Network Based Life Cycle Assessment Model for Product Concepts Using Product Classification Method , 2005, ICCSA.

[8]  Zhenhua Wu,et al.  Application of neural network on environmental impact assessment tools , 2008 .

[9]  T. Wieczorek,et al.  Comparison of feature ranking methods based on information entropy , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[10]  Jules Thibault,et al.  Process modeling with neural networks using small experimental datasets , 1999 .

[11]  Maracin S. Szczuka.  Advances in Hybrid Information Technology, First International Conference, ICHIT 2006, Jeju Island, Korea, November 9-11, 2006, Revised Selected Papers , 2007, ICHIT.